code: def _get_parameters_hist_gbdt(trees, extra_config):
      """
      Extract the tree parameters from SklearnHistGradientBoostingClassifier trees
      Args:
          trees: The information representing a tree (ensemble)
          Returns: The tree parameters wrapped into an instance of `operator_converters._tree_commons_TreeParameters`
      """
      features = [n["feature_idx"] for n in trees.nodes]
      try:
          thresholds = [
              n["threshold"] if n["threshold"] != 0 else -1
              for n in trees.nodes
          ]
      except ValueError:
          # newer version of scikit-learn
          thresholds = [
              n["num_threshold"] if n["num_threshold"] != 0 else -1
              for n in trees.nodes
          ]
      lefts = [n["left"] if n["left"] != 0 else -1 for n in trees.nodes]
      rights = [
          n["right"] if n["right"] != 0 else -1 for n in trees.nodes
      ]
      values = [
          [n["value"]] if n["value"] != 0 else [-1] for n in trees.nodes
      ]
  
      return TreeParameters(lefts, rights, features, thresholds, values)
  
file_path: hummingbird/hummingbird/ml/operator_converters/sklearn/gbdt.py
imports: import numpy
  from onnxconverter_common.registration import register_converter
  from ..None import constants
  from .._gbdt_commons import convert_gbdt_common, convert_gbdt_classifier_common
  from .._tree_commons import get_parameters_for_sklearn_common, get_parameters_for_tree_trav_sklearn, TreeParameters
label_desc: Use image node_id 2 for calling a global function with example usage: _get_parameters_hist_gbdt(trees, extra_config) and returns: TreeParameters